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This paper presents an automated recognition and classification technique for the various power quality disturbances. This technique is based on S-transform and MLP based neural network. The distorted voltage waveforms are generated using Matlab simulation on the test system. The S-Transform method is introduced as a powerful tool for the input feature extraction from the distorted voltage waveforms. The extracted features are applied as the inputs to the MLP based neural network for classification of various classes of power quality disturbances. For each class of disturbances MLP based neural network has been trained at the rate of 100 samples. The algorithm has been tested with 900 number of test data and the outcomes are recorded. The performance of the proposed technique has been evaluated by comparing the results against S-transform based fuzzy expert system.

Power Quality Disturbances Classification and Recognition Using S-transform Based Neural classifier